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Field
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Computer Science, Biomedical Engineering, Bioinformatics, or a related field. Required: Strong understanding of machine learning (ML) and deep learning (DL) methods, with hands-on experience in model development and
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research program. The research is expected to be in one of several broad areas: statistical machine learning, statistical problems in AI, large language models, etc. Successful candidates will prepare and
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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a position combining project management, machine-learning model development, data management/analysis, and manuscript writing for publication. Preference will be given to applicants with (1
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged
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characteristics of obligate intracellular bacteria, including Ehrlichia and Neorickettsia spp. We use a mouse model to study the disease pathogenesis in the mammalian hosts. We also work with blood samples
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Spectroscopy (dwSCOS) sensor for non-invasive microvascular monitoring. 2. Perform Monte Carlo simulations for optical modeling of photon propagation in layered tissues. 3. Fabricate and characterize dynamic
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d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
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of obligate intracellular bacteria, including Ehrlichia and Neorickettsia spp. We use a mouse model to study the disease pathogenesis in the mammalian hosts. We also work with blood samples collected from